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How to use AI to create internal training step by step
Applying artificial intelligence to training does not require a technical profile or a multinational-sized budget. It requires a plan, a starting piece of content, and a tool that does the heavy lifting for you.
You’ve been hearing about artificial intelligence in training for months. You’ve seen demos, read articles, and maybe even tested a chatbot. But when it comes to applying AI to your training program, the question is still the same: where do I start?
You’re not alone. Many HR teams are at that point: they know AI can save time and improve their content, but they’re not clear on the first step. And that uncertainty slows adoption more than any technical limitation.
The reality is that getting started with AI in training is simpler than it seems. You don’t need a tech team, a special budget, or a master’s degree in machine learning. You need to understand what content you have, what problem you want to solve, and follow a structured process.
In this article, we give you a practical five-step guide to creating AI-powered training, from auditing your current content to measuring results. Designed for HR professionals who want to move from theory to action.
If you’re still wondering whether it’s too early to bring AI into training, the data says otherwise.
In 2025, 20% of companies in the European Union were already using AI technologies, almost double the previous year.¹ And this is not just a large-corporation trend: European SMEs are accelerating adoption thanks to accessible tools that don’t require their own infrastructure.
In the specific field of training, 91% of companies plan to increase their investment in AI for L&D in 2026.² The reason is practical: organizations already using AI in training report a 40% reduction in the time needed to create and deploy content, while maintaining the same level of effectiveness.³
Meanwhile, traditional formats keep losing ground. PDF manuals, static presentations, and long recordings generate increasingly lower completion rates. If you want to understand why, this article on why nobody reads training PDFs explains it with data.
The context is clear: AI is no longer experimental, and teams that don’t start now will have to catch up under worse conditions next year.
Before choosing a tool or creating anything new, you need to know what you already have. It sounds obvious, but most HR teams don’t have a clear inventory of their training materials.
List everything you use to train people: PDFs, presentations, manuals, recorded videos, onboarding guides, compliance documents. Everything.
Once you have the inventory, classify each item according to three criteria:
The guiding question is simple: which content do you update most often and share with the most people? Start there. Remember, AI doesn’t create strategy for you: it amplifies what is already well thought out and accelerates what is already structured.
AI is not a generic solution. It can do many things, but trying to use it for everything at once is the fastest way to stall the project.
There are three main uses of AI in internal training:
Create new content. Generate video modules from a script or document, create automatic voiceovers, design dynamic presentations. Useful when you need to produce content that doesn’t yet exist.
Adapt existing content. Translate into other languages, update data or regulations, convert a PDF into an interactive module. Useful when you already have the content but the format doesn’t work.
Measure and optimize. Analyze how training is consumed, identify drop-off points, understand which modules generate the most engagement. Useful when you already produce content but don’t know whether it works.
Our advice: choose one of the three and start there. If you have a lot of outdated content, start with adaptation. If you produce little because the process is slow, start with creation. If you produce a lot but lack visibility, start with measurement.
Don’t try to solve all three problems at once. A focused pilot generates faster and easier-to-defend results.
Once you’re clear on what you need, it’s time to look for a tool. And this is where many teams get lost: too many options, too many promises, not enough clear criteria.
If you don’t have a technical profile, focus on three things:
Beyond these filters, there are more detailed criteria worth reviewing. In this guide on how to choose an AI tool for internal training, we break them down into a 10-question checklist before signing.
This is where everything becomes tangible. And where many teams freeze, because they feel they need to create something perfect from scratch.
You don’t. The best starting point is a document you already have. An onboarding manual, a compliance guide, an internal procedure. Something that already exists in text or presentation format and needs to reach many people.
The typical process:
A well-executed pilot in a specific use case is more valuable than an ambitious project that never launches. Start small, measure, and decide with data.
The pilot is not the end. It’s the beginning of the cycle.
Compare results from the AI-generated module with the previous format. Has completion improved? Is the average consumption time reasonable? Do employees rate it better?
If the data is positive, adjust what’s needed (duration, tone, structure) and scale to more content. If not, analyze why and test another approach before expanding.
Companies that measure the impact of their training are 27% more likely to report market share growth.⁴ Measurement is not an add-on; it’s what turns a test into a strategy.
Scaling doesn’t mean transforming everything at once. It means having a validated process you can replicate: audit → define use case → create module → measure → repeat. Once refined, that cycle is what differentiates teams that truly use AI from those that only tested it once.
We’ve seen these mistakes across dozens of teams. They’re easy to avoid if you know them in advance.
Trying to automate everything at once. The temptation is strong: if AI can create modules in minutes, why not transform everything? Because without validation, you scale mistakes too. Start with one case, validate, then grow.
Choosing a tool based on feature lists. Demos are impressive, but the real question is: does it solve your specific problem? A five-person HR team doesn’t need the same solution as a multinational L&D department. In this article on using AI in internal training, we explain how to identify the processes that benefit most.
Not involving the training team from the start. If trainers feel AI is replacing them, resistance will follow. AI doesn’t replace the trainer: it frees them from repetitive production tasks so they can focus on design, not editing.
Ignoring measurement. Creating AI content without measuring impact is the modern equivalent of uploading PDFs to an LMS and calling it done. AI without data is just faster production, not better training.
Assuming AI means no supervision. AI-generated modules require human review. Content must be accurate, aligned with company culture, and appropriate for the audience. AI accelerates production, but quality remains the team’s responsibility.
The first step is not choosing a tool. It’s looking at what you already have and deciding which problem to solve first.
Applying AI to training is not a massive digital transformation project that requires months of planning. It’s an operational shift that starts with one document, one tool, and one metric. The teams that achieve the best results are not the most technical; they are the ones with a clear process: audit, define, create, measure, scale.
Tools like Vidext are designed so HR teams without technical profiles can transform their content into interactive video modules, with automatic translation and integrated consumption analytics. No external production, no steep learning curve.
If you have an onboarding PDF no one opens or a compliance manual you update three times a year, you already have the perfect starting point. In five years, companies won’t compete on having more training content, but on having their internal knowledge better structured. AI is the accelerator of that shift.
No. Current AI tools for training are designed for non-technical profiles. If you can use a presentation editor, you can create modules with AI. The learning curve is minimal.
It depends on complexity, but a 5-minute video module based on existing text can be ready in under an hour, including review. Without AI, the same content would take days or weeks to produce.
No, and it shouldn’t. AI automates content production (voiceover, video, translation), but instructional design, pedagogical strategy, and quality control remain human responsibilities. AI frees up time; it doesn’t replace judgment.
Content that updates frequently (compliance, product, internal policies), that needs to reach many people (onboarding), or that must exist in multiple languages. The more repetitive the production process, the greater the benefit of AI.
It depends on the tool. Look for providers that comply with GDPR, hold security certifications (such as ISO 27001), and do not use your content to train their models. Data security should be a selection criterion, not an afterthought.
The range is broad. Professional tools for corporate teams typically cost between €5,000 and €15,000 per year, depending on content volume and users. But the real calculation must include savings in team hours and external production, which often exceed the license cost.
By comparing metrics before and after: completion rate, time spent per module, drop-off points, and—if possible—impact on employee performance. If your tool doesn’t provide these data points, you can’t know.
¹ Use of artificial intelligence in enterprises - Eurostat
² Top 40 AI Training Stats in 2026 - VirtualSpeech
³ eLearning Statistics for 2026 - iSpring
⁴ 2025 Training Industry Report - Training Magazine
@ 2026 Vidext Inc.
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